Senior Software Engineer - Performance Prediction

Latitude AI; United States; On-site; USD 161,280 - 268,800; Full time

Benefits offered by this job

Medical insurance

401(k) plan

Parental leave

Unlimited vacation

Wellness stipend

Job summary

Latitude AI is building the future of Ford’s autonomy roadmap, delivering a hands-free ADAS platform to Ford’s 2027 EV rollout. The team blends ML research with scalable production systems to enable safe, reliable autonomous driving predictions.

The role focuses on ML systems development, model evaluation, and internal tooling, collaborating with autonomy, simulation, and infrastructure teams to push innovations into production. California-based, with competitive compensation and strong benefits.

Qualifications

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field with 4+ years of experience (or MS/PhD).
• Strong Python software engineering experience in modular, well-tested systems.
• Experience developing, training, tuning, productionizing supervised ML models.
• Solid grasp of statistics and experimental design for trustworthy results.
• Experience with ML tooling (PyTorch, scikit-learn) and large datasets (SQL, pandas, NumPy).
• Excellent cross-team communication across software, ML, and autonomy groups.

Responsibilities

• Build production software for model training, offline evaluation, and release-review workflows.
• Develop and improve learned models for performance prediction and probabilistic forecasting.
• Design training/validation/holdout strategies for trustworthy model evaluation.
• Define metrics (precision, recall, F1, ROC-AUC, calibration) and monitor them.
• Run experiments, tune models, and analyze results with rigorous statistics.
• Create internal tools to compare software versions and inspect model outputs.
• Collaborate with autonomy, simulation, and infrastructure teams to move ideas to production.
• Improve engineering quality through testing, CI, and clear interfaces across data, modeling, and product layers.

Skills

Python

ML systems

Statistics

PyTorch

SQL/Pandas/NumPy

Communication

Education

Bachelor's degree in Computer Engineering/CS/EE/Robotics

Tools

PyTorch

scikit-learn

Dagster

Airflow

Weights & Biases

Dash

Plotly

Streamlit

Bazel

Job description

Latitude AI (lat.ai) is building the future of Ford’s autonomy roadmap to make travel safer, less stressful, and more enjoyable for everyone. Bringing this vision to scale, our fully in-house developed hands-free ADAS platform will debut on Ford’s all-new Universal Electric Vehicle in 2027.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to redefining the relationship between people and their vehicles for millions of customers.

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Performance Prediction team builds the Machine Learning models, evaluation pipelines, and internal tools that help us understand how autonomy behavior changes across software releases. We work on problems that span behavior classification, ride quality detection, probabilistic trajectory prediction, and release regression analysis.

Our systems support both classical and modern ML approaches. That includes compact learned classifiers such as tree-based models for behavior and ride quality detection, as well as deep learning-based probabilistic prediction models for more complex autonomy tasks. We also build the software around those models: dataset definition, feature generation, training and tuning workflows, offline metrics, experiment tracking, and tools that help engineers inspect regressions at the slice and scenario level.

This role is a strong fit for someone who enjoys building reliable Python systems and applying rigorous ML evaluation methods in a safety-critical domain. In practice, the work is a mix of ML systems development, model and evaluation work, and internal tooling used by partner teams across autonomy.

What you’ll do:

• Build production software for model training, offline evaluation, and release-comparison workflows
• Develop and improve learned models for performance prediction, including behavior classifiers and probabilistic prediction models
• Design training, validation, and holdout strategies that produce trustworthy results
• Define and track model and release metrics such as precision, recall, F1, ROC AUC, calibration quality, and task-specific forecasting metrics
• Run experiments, tune models, and analyze results with strong statistical rigor
• Build internal tools that help engineers compare software versions, inspect model outputs, and investigate regressions
• Partner with autonomy, simulation, and infrastructure teams to move ideas from prototype to production
• Raise engineering quality through testing, code review, CI, and maintainable interfaces across data, modeling, and product layers

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong software engineering skills in Python, including experience building modular, maintainable, well-tested systems in a shared codebase
• Experience developing, training, tuning, or productionizing supervised ML models
• Strong grounding in statistics and experimental design, including experience designing model training and evaluation tests
• Experience selecting and interpreting model metrics, thresholds, and tradeoffs for real-world decision-making
• Experience with ML tooling such as PyTorch, scikit-learn, or similar frameworks
• Experience working with large datasets using SQL, pandas, and NumPy
• Strong communication skills and the ability to work effectively across software, ML, and autonomy teams

Nice to have:

• PhD in Computer Science, Machine Learning, Statistics, Robotics, or a closely related field is preferred
• Equivalent research-heavy industry experience is highly valued
• Experience with probabilistic forecasting, trajectory prediction, sequential modeling, or graph-based models
• Experience with classical ML methods such as random forests, gradient boosting, or calibrated linear models
• Experience with calibration, uncertainty estimation, ablation studies, error analysis, or release regression methodology
• Experience building internal analytics or ML tools with Dash, Plotly, Streamlit, or similar frameworks
• Experience with workflow orchestration or experimentation tools such as Dagster, Airflow, or Weights and Biases
• Experience with Bazel or other large-scale build systems
• Prior autonomous driving experience is helpful but not required. Strong experience with production ML systems and rigorous model evaluation is sufficient

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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